Top Hybrid Data & Analytics Jobs

As a Senior Data Engineer, you'll design and optimize data systems and pipelines, lead integrations, ensure data quality, and collaborate with cross-functional teams to enhance data infrastructure.

Design enterprise-grade data solutions using Databricks and Azure, optimize data pipelines, ensure compliance, and lead integration architecture efforts.

The GenAI Tuning Analyst improves Generative AI performance in contact centers through data analysis, prompt engineering, and collaboration with SMEs.

Provide second-level support for EDI clients, troubleshoot issues, and script medical billing conversions to meet claims requirements using proprietary scripting techniques.

The Data Architect will design and implement data architecture strategies, ensuring data assets are structured, accessible, and secure while collaborating with stakeholders and supporting federal law enforcement data initiatives.

Intern will assist the Talent Acquisition team by building and analyzing metrics, creating dashboards, and exploring data workflows to support global recruiting operations.

The role involves project management, efficiency analysis, quality assurance, and systems management with a focus on improving operational workflows and processes.

Design, build, and maintain scalable data pipelines and ETL workflows using Python, Snowflake, DBT, Fivetran, and Amazon DMS. Integrate APIs and streaming data (Kafka), orchestrate with Airflow, and deploy containerized solutions with Docker and Kubernetes. Monitor, optimize, and collaborate across teams to ensure reliable, high-quality data delivery.

Designs and implements an enterprise data governance framework, establishes standards and stewardship, leads data cleanup, ensures compliance with financial regulations, integrates governance into agile data products, and trains stakeholders to drive data quality and democratization.

Support RevOps by building and maintaining dashboards, ensuring revenue data accuracy, preparing executive and Board reporting, conducting ad hoc analyses, identifying data quality issues, and communicating insights to technical and non-technical stakeholders.